I bumped into a professional acquaintance last week. After describing briefly a presentation I was about to give, he offered to broker introductions to others who might have an interest in the work I’ve been doing. To initiate the introductions, I crafted a brief description of what I’ve been up to for the past 5 years in this area. I’ve also decided to share it here as follows:

As always, [name deleted], I enjoyed our conversation at the recent AGU meeting in Toronto. Below, I’ve tried to provide some context for the work I’ve been doing in the area of knowledge representations over the past few years. I’m deeply interested in any introductions you might be able to broker with others at York who might have an interest in applications of the same.

Since 2004, I’ve been interested in expressive representations of data. My investigations started with a representation of geophysical data in the eXtensible Markup Language (XML). Although this was successful, use of the approach underlined the importance of metadata (data about data) as an oversight. To address this oversight, a subsequent effort introduced a relationship-centric representation via the Resource Description Format (RDF). RDF, by the way, forms the underpinnings of the next-generation Web – variously known as the Semantic Web, Web 3.0, etc. In addition to taking care of issues around metadata, use of RDF paved the way for increasingly expressive representations of the same geophysical data. For example, to represent features in and of the geophysical data, an RDF-based scheme for annotation was introduced using XML Pointer Language (XPointer). Somewhere around this point in my research, I placed all of this into a framework.

A data-centric framework for knowledge representation.

In addition to applying my Semantic Framework to use cases in Internet Protocol (IP) networking, I’ve continued to tease out increasingly expressive representations of data. Most recently, these representations have been articulated in RDFS – i.e., RDF Schema. And although I have not reached the final objective of an ontological representation in the Web Ontology Language (OWL), I am indeed progressing in this direction. (Whereas schemas capture the vocabulary of an application domain in geophysics or IT, for example, ontologies allow for knowledge-centric conceptualizations of the same.)

From niche areas of geophysics to IP networking, the Semantic Framework is broadly applicable. As a workflow for systematically enhancing the expressivity of data, the Framework is based on open standards emerging largely from the World Wide Web Consortium (W3C). Because there is significant interest in this next-generation Web from numerous parties and angles, implementation platforms allow for increasingly expressive representations of data today. In making data actionable, the ultimate value of the Semantic Framework is in providing a means for integrating data from seemingly incongruous disciplines. For example, such representations are actually responsible for providing new results – derived by querying the representation through a ‘semantified’ version of the Structured Query Language (SQL) known as SPARQL.

I’ve spoken formally and informally about this research to audiences in the sciences, IT, and elsewhere. With York co-authors spanning academic and non-academic staff, I’ve also published four refereed journal papers on aspects of the Framework, and have an invited book chapter currently under review – interestingly, this chapter has been contributed to a book focusing on data management in the Semantic Web. Of course, I’d be pleased to share any of my publications and discuss aspects of this work with those finding it of interest.

With thanks in advance for any connections you’re able to facilitate, Ian.

… join us for an exciting national summit on innovation and technology, hosted by ORION and CANARIE, at the Metro Toronto Convention Centre, Nov. 3 and 4, 2008.

“Powering Innovation – a National Summit” brings over 55 keynotes, speakers and panelist from across Canada and the US, including best-selling author of Innovation Nation, Dr. John Kao; President/CEO of Intenet2 Dr. Doug Van Houweling; chancellor of the University of California at Berkeley Dr. Robert J. Birgeneau; advanced visualization guru Dr. Chaomei Chen of Philadelphia’s Drexel University; and many more. The President of the Ontario College of Art & Design’s Sara Diamond chairs “A Boom with View”, a session on visualization technologies. Dr. Gail Anderson presents on forensic science research. Other speakers include the host of CBC Radio’s Spark Nora Young; Delvinia Interactive’s Adam Froman and the President and CEO of Zerofootprint, Ron Dembo.

This is an excellent opportunity to meet and network with up to 250 researchers, scientists, educators, and technologists from across Ontario and Canada and the international community. Attend sessions on the very latest on e-science; network-enabled platforms, cloud computing, the greening of IT; applications in the “cloud”; innovative visualization technologies; teaching and learning in a web 2.0 universe and more. Don’t miss exhibitors and showcases from holographic 3D imaging, to IP-based television platforms, to advanced networking.

Juniper has a comprehensive portfolio of offerings at the intersection of security and networking. Interestingly, Juniper’s Security Threat Response Manager (STRM) OEMs technology from Q1Labs.

802.1x is a solid bet. Based on a number of trends, and a variety of requirements, Juniper promotes use of 802.1x. Even though this is a path we’ve already identified, it’s good to have it independently validated …

Security, and other services, can be offloaded to purpose-built devices in the core. Instead of inserting, e.g., a FWSM into a device (e.g., a Cisco 65xx) that is primarily providing routing and switching services, Juniper has recently introduced a new paradigm with its SRX series. Touted as a services gateway for the core, the purpose of the SRX is to offload from the routing/switching devices various services – e.g., firewall, VPN, etc. As I understand it, the SRX runs JUNOS with various enhancements from ScreenOS (their O/S from their firewall devices). Even if you don’t make use of Juniper solutions, it may make sense to understand and potentially apply the offloading-of-services concept/paradigm in your core.

Juniper allows for the virtualization of switches. Juniper Virtual Chassis (VC) is currently only available for their EX 4200 platform. With VC, it’s possible to virtualize up to 10 physically distinct EX 4200s into one. Within the next year, Juniper plans to provide VC on, e.g., their EX 8200 platform. Because vmWare’s vMotion requires layer-2 adjacency, server virtualization may prove to be a significant driver for switch virtualization. I expect that this will prove, e.g., to be particularly relevant in providing failover services (at the networking layer) between multiple, physically distinct, and geographically separated locations.

Even though the event appeared to be more of the sales-y/marketing-y variety, there was substantial technical content in evidence.

RDF-ization is a term used by the Semantic Web community to describe the process of generating RDF from non RDF Data Sources such as (X)HTML, Weblogs, Shared Bookmark Collections, Photo Galleries, Calendars, Contact Managers, Feed Subscriptions, Wikis, and other information resource collections.

Although Idehen identifies a number of data sources, he does not explicitly identify two data sources I’ve been spending a fair amount of time with over the past few years:

Of course, whether the motivation is personal/social-networking or scientific/IT related, the attention to RDF-ization is win-win for all stakeholders. Why? Anything that accelerates the RDF-ization of non-RDF data sources brings us that much closer to realizing the true value of the Semantic Web.

From the Core to the Edge: Automating Awareness of Network Topology through Knowledge Representation

Abstract

Like many other institutions of higher education, York University makes extensive use of Open Source software. This is especially true in the case of monitoring and managing IP (Internet Protocol) devices. On the monitoring front, extensive manual configuration is currently required to make monitoring solutions (e.g., NAGIOS) aware of the topology of the York network. And with respect to managing, NetDisco automatically discovers assets placed on the network, but is unable to abstract away unnecessary complexity in, e.g., rendering schematics of the network topology. These and other examples suggest that NAGIOS and NetDisco operate in the realm of data, and possibly information, but are unable to envisage network topology from a knowledge-representation perspective. Thus the current focus is on applying a recently developed knowledge-representation platform to such routine requirements in network monitoring and management. The platform is based on Sematic Web standards and implementations and has already been proven effective in various scientific contexts. Ultimately our objective is to extract data automatically discovered by NetDisco, represent it using the knowledge-based platform, and transform a topology-aware representation of the data into configuration data that can be ingested by NAGIOS.

What’s interesting [now] is that there is an emergent new model, and you all are here because you are part of that new model. I don’t think people have really understood how big this opportunity really is. It starts with the premise that the data services and architecture should be on servers. We call it cloud computing – they should be in a “cloud” somewhere. And that if you have the right kind of browser or the right kind of access, it doesn’t matter whether you have a PC or a Mac or a mobile phone or a BlackBerry or what have you – or new devices still to be developed – you can get access to the cloud. There are a number of companies that have benefited from that. Obviously, Google, Yahoo!, eBay, Amazon come to mind. The computation and the data and so forth are in the servers.

My interpretation of cloud computing is summarized in the following figure.